CN107561036B - Rhizoma bletillae variety and authenticity detection method - Google Patents
Rhizoma bletillae variety and authenticity detection method Download PDFInfo
- Publication number
- CN107561036B CN107561036B CN201710757065.4A CN201710757065A CN107561036B CN 107561036 B CN107561036 B CN 107561036B CN 201710757065 A CN201710757065 A CN 201710757065A CN 107561036 B CN107561036 B CN 107561036B
- Authority
- CN
- China
- Prior art keywords
- powder
- sample
- bletilla striata
- spectrum
- rhizoma bletillae
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000001514 detection method Methods 0.000 title abstract description 10
- 241001313857 Bletilla striata Species 0.000 claims abstract description 36
- 239000000843 powder Substances 0.000 claims abstract description 21
- 238000001228 spectrum Methods 0.000 claims abstract description 16
- 239000000463 material Substances 0.000 claims abstract description 10
- 238000004364 calculation method Methods 0.000 claims abstract description 5
- 238000009795 derivation Methods 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims abstract description 5
- 230000009466 transformation Effects 0.000 claims abstract description 5
- 238000004497 NIR spectroscopy Methods 0.000 claims abstract description 4
- 238000004458 analytical method Methods 0.000 claims abstract description 3
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 3
- 241001313855 Bletilla Species 0.000 claims description 18
- 238000000034 method Methods 0.000 claims description 14
- 230000008901 benefit Effects 0.000 abstract description 3
- 238000007621 cluster analysis Methods 0.000 description 4
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 3
- 238000007781 pre-processing Methods 0.000 description 2
- 239000010453 quartz Substances 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 208000034507 Haematemesis Diseases 0.000 description 1
- 208000000616 Hemoptysis Diseases 0.000 description 1
- 241000233855 Orchidaceae Species 0.000 description 1
- 206010040849 Skin fissures Diseases 0.000 description 1
- 206010053476 Traumatic haemorrhage Diseases 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000005469 granulation Methods 0.000 description 1
- 230000003179 granulation Effects 0.000 description 1
- 230000002439 hemostatic effect Effects 0.000 description 1
- 235000008216 herbs Nutrition 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000001320 near-infrared absorption spectroscopy Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000001028 reflection method Methods 0.000 description 1
- 238000007873 sieving Methods 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000008961 swelling Effects 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
- 229940126680 traditional chinese medicines Drugs 0.000 description 1
Images
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a detection method of bletilla striata varieties, which adopts near infrared spectroscopy for detection and comprises the following steps: taking medicinal material powder to be detected, loading a sample, collecting a near infrared spectrum, performing standard normal variable transformation processing on an original spectrum by adopting a clustering analysis as a calculation method, performing spectrum pretreatment by combining nine-point convolution derivation, and identifying a bletilla striata variety by using a score of a main component of the sample. The detection method of the bletilla striata varieties has the advantages of high accuracy, convenience in operation, low cost and good market application prospect.
Description
Technical Field
The invention relates to a bletilla striata variety and a method for detecting authenticity, and belongs to the field of traditional Chinese medicines.
Background
Bletilla striata is a dried tuber of the plant Bletilla striata (Thunb.) reichb.f. of the family orchidaceae. Has astringent, hemostatic, repercussive, and granulation promoting effects. The efficacy of (1). Can be used for treating hemoptysis, hematemesis, traumatic hemorrhage, pyocutaneous disease, toxic swelling, and chapped skin. There are 4 major species in china, Bletilla striata (Thunb.) reichb.f., Bletilla striata ochracea (Bletilla) Schltr., Bletilla striata sinensis (Rolfe) Schltr., and Bletilla striata fortiana (Hayata) Schltr.
At present, the common bletilla pseudobulb variety identification method mainly adopts the traditional methods of appearance observation, physicochemical identification, microscopic characteristic observation and the like. However, the original appearance characteristics of the crushed bletilla striata powder disappear, and the traditional identification method cannot distinguish the variety source of the bletilla striata powder.
A simpler, more convenient, more accurate and more reliable method for identifying the bletilla striata varieties needs to be found.
Disclosure of Invention
In order to solve the problems, the invention provides a method for detecting bletilla striata varieties.
The invention relates to a method for detecting bletilla striata varieties, which adopts near infrared spectroscopy to detect and comprises the following steps:
(1) taking medicinal material powder to be detected, loading a sample, and collecting a near infrared spectrum;
(2) and (3) performing standard normal variable transformation processing on the original spectrum by using cluster analysis as a calculation method, performing spectrum pretreatment by combining nine-point convolution derivation, and identifying the bletilla striata varieties by using the score values of the main components of the sample.
Further, in step (1), the spectrum collection conditions are: resolution 8cm-1Scanning times of 64 times and a scanning range of 4000-10000cm-1Each sample was loaded and scanned 3 times in duplicate.
Further, in step (1), the scanning range is: 4400-4800cm-1、5400-6600cm-1And 7800 + 10000cm-1。
Further, in the step (2), the main component is PC 1.
Further, in step (2), the score of the PC1 is:
and (3) common bletilla pseudobulb powder: 0.0590-0.1901; common bletilla pseudobulb powder: -0.2295~ 0.0393.
Further, the common bletilla pseudobulb powder is common bletilla pseudobulb powder or small common bletilla pseudobulb powder.
The detection method of the bletilla striata varieties can accurately detect the varieties of bletilla striata medicinal materials to be detected, has high accuracy, is simple and quick, can replace the traditional detection method, and has good application prospect.
Obviously, many modifications, substitutions, and variations are possible in light of the above teachings of the invention, without departing from the basic technical spirit of the invention, as defined by the following claims.
The present invention will be described in further detail with reference to the following examples. This should not be understood as limiting the scope of the above-described subject matter of the present invention to the following examples. All the technologies realized based on the above contents of the present invention belong to the scope of the present invention.
Drawings
FIG. 1 is the original map of NIRS of 40 batches of samples in example 2 of the present invention.
Fig. 2 is a two-dimensional score chart of main components of bletilla striata and congeneric medicinal materials in example 2 of the present invention, wherein 1 is congeneric bletilla striata, and 2 is bletilla striata.
Fig. 3 is a three-dimensional score chart of main components of bletilla striata and congeneric medicinal materials in example 2 of the present invention, wherein 1 is congeneric bletilla striata, and 2 is bletilla striata.
Detailed Description
Instrument for measuring the position of a moving object
NIR Flex N-500 near Infrared Spectroscopy, Quartz glass sample cell and rotator Diffuse reflection integrating sphere, NIRcal5.4 data analysis processing software (Buchi Labortechnik AG)
Medicinal materials
40 samples of Bletilla striata in Sichuan, Guizhou and other areas are collected or collected, 18 samples of Bletilla striata Bletilla striata (Thunb.) Reichb. f. sample, 19 samples of Bletilla striata Bletilacaceae Schltr. sample and 3 samples of Bletilla striata Bletillamomana (Hayata) Schltr. sample are identified by DNA barcode ITS2 sequence, and the specific information of the samples is shown in the following Table 1.
TABLE 1 sample information Table
Example 1 detection of bletilla striata species
(1) Bletilla striata variety detection method
Taking the powder of the medicinal material to be detected, placing the powder into a quartz sample cup, uniformly and flatly paving the powder, and selecting 4400--1Scanning 3 wave bands, adopting cluster analysis as a calculation method, performing standard normal variable transformation processing on an original spectrum, performing spectrum pretreatment by combining nine-point convolution derivation, and finally identifying bletilla striata varieties by using the score value of a main component PC1, wherein the PC1 value of bletilla striata powder is 0.0590-0.1901; the common bletilla pseudobulb powder has a PC1 value of-0.2295-0.0393.
(2) Authentication
Different purchased rhizoma bletillae varieties are adopted for verification, the accuracy of the rhizoma bletillae variety detection method is up to 90%, and the method can be used for accurately identifying the rhizoma bletillae varieties and is convenient to operate.
Example 2 selection of parameters in bletilla striata variety identification
(1) Atlas information gathering
Drying and crushing medicinal materials, sieving the medicinal materials by a 100-mesh sieve, putting about 8g of sample powder into a quartz sample cup, uniformly and flatly paving the sample cup, and collecting a spectrum by an integrating sphere diffuse reflection method according to the following conditions: resolution 8cm-1Scanning 64 times, spectrum scanning range 4000-10000cm-1Repeat for each sampleThe sample is loaded and scanned 3 times, and the acquired atlas is shown in figure 1.
(2) Parameter screening
And (3) introducing the collected 40 batches of sample spectra into self-contained analysis software NIRcal of the instrument, dividing a calibration set (C-set) and a verification set (V-set) of the samples according to the ratio of 2:1, and analyzing after sample diversity is finished.
By screening the scanning wave band, the analysis method, the spectrum preprocessing method and the principal component number, the factors which have small contribution to the cluster analysis map are removed, the optimal parameters are preferably selected according to the comprehensive evaluation index (Q value), the principal component two-dimensional score map and the principal component three-dimensional score map, and the results are shown in table 2.
TABLE 2 parameter data
As can be seen from Table 2, the scanning ranges of the present invention are 4400--13 wave bands can be well detected, the original spectrum is subjected to standard normal variable transformation (SNV) processing by adopting Cluster analysis (Cluster) as a calculation method, and spectrum preprocessing is performed by combining nine-point convolution derivation (dg 2).
The two-dimensional and three-dimensional scores of the main components of rhizoma Bletillae and the same genus of herbs are shown in Table 3, FIG. 2 and FIG. 3.
TABLE 3 principal Components score
It can be seen that the common bletilla pseudobulb, the common genus common bletilla pseudobulb and the small common bletilla pseudobulb can be obviously clustered into 2 groups which are mutually independent by the treatment method. The common bletilla pseudobulb, the common bletilla pseudobulb and the small common bletilla pseudobulb have obvious difference in information carrying capacity on PC1, so that the common bletilla pseudobulb and the common bletilla pseudobulb can be distinguished.
In conclusion, the method for detecting the bletilla striata varieties can accurately identify the authenticity and the varieties of the bletilla striata, has the advantages of accuracy, simplicity and convenience in operation, low cost and good application prospect and economic benefit.
Claims (3)
1. A method for detecting bletilla striata varieties adopts near infrared spectroscopy, and comprises the following steps:
(1) taking medicinal material powder to be detected, loading a sample, and collecting a near infrared spectrum;
(2) performing standard normal variable transformation processing on an original spectrum by adopting a clustering analysis as a calculation method, performing spectrum pretreatment by combining nine-point convolution derivation, and identifying rhizoma bletillae varieties by using score values of sample principal components;
in the step (1), the scanning range is as follows: 4400--1、5400-6600 cm-1And 7800 + 10000cm-1；
In the step (2), the main component is PC 1;
in the step (2), the score value of the PC1 is:
and (3) common bletilla pseudobulb powder: 0.0590-0.1901; common bletilla pseudobulb powder: -0.2295~ 0.0393.
2. The method of claim 1, wherein: in the step (1), the spectrum collection conditions are as follows: resolution 8cm−1The number of scans was 64, and each sample was loaded and scanned 3 times in duplicate.
3. The method of claim 1, wherein: the rhizoma Bletillae congeneric powder is rhizoma Bletillae powder and small rhizoma Bletillae powder.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710545286 | 2017-07-06 | ||
| CN2017105452865 | 2017-07-06 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107561036A CN107561036A (en) | 2018-01-09 |
| CN107561036B true CN107561036B (en) | 2020-02-28 |
Family
ID=60977451
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710757065.4A Expired - Fee Related CN107561036B (en) | 2017-07-06 | 2017-08-29 | Rhizoma bletillae variety and authenticity detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107561036B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111007032B (en) * | 2019-11-13 | 2023-01-03 | 上海长海医院 | Near-infrared spectroscopy for rapidly and nondestructively identifying liquorice and pseudo-product glycyrrhiza spinosa |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004079347A1 (en) * | 2003-03-07 | 2004-09-16 | Pfizer Products Inc. | Method of analysis of nir data |
| CN104655678A (en) * | 2014-12-16 | 2015-05-27 | 谢绍鹏 | Method for rapidly identifying fritillary varieties and adulteration of unibract fritillary bulb |
| CN104655812A (en) * | 2014-12-16 | 2015-05-27 | 谢绍鹏 | Method for rapidly identifying trueness and quality of radix notoginseng |
| CN105092725A (en) * | 2014-05-16 | 2015-11-25 | 成都中医药大学 | Alpine gentian herb HPLC detection method |
| CN105138861A (en) * | 2015-05-31 | 2015-12-09 | 青岛市食品药品检验研究院 | Building method for rhubarb medicinal material trueness/falseness and species prediction model |
| CN106568740A (en) * | 2016-10-31 | 2017-04-19 | 湖北省农业科学院果树茶叶研究所 | Method for rapid judging of varieties of fresh tea leaves by near infrared spectroscopy |
-
2017
- 2017-08-29 CN CN201710757065.4A patent/CN107561036B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004079347A1 (en) * | 2003-03-07 | 2004-09-16 | Pfizer Products Inc. | Method of analysis of nir data |
| CN105092725A (en) * | 2014-05-16 | 2015-11-25 | 成都中医药大学 | Alpine gentian herb HPLC detection method |
| CN104655678A (en) * | 2014-12-16 | 2015-05-27 | 谢绍鹏 | Method for rapidly identifying fritillary varieties and adulteration of unibract fritillary bulb |
| CN104655812A (en) * | 2014-12-16 | 2015-05-27 | 谢绍鹏 | Method for rapidly identifying trueness and quality of radix notoginseng |
| CN105138861A (en) * | 2015-05-31 | 2015-12-09 | 青岛市食品药品检验研究院 | Building method for rhubarb medicinal material trueness/falseness and species prediction model |
| CN106568740A (en) * | 2016-10-31 | 2017-04-19 | 湖北省农业科学院果树茶叶研究所 | Method for rapid judging of varieties of fresh tea leaves by near infrared spectroscopy |
Non-Patent Citations (4)
| Title |
|---|
| 红外及近红外光谱法对真伪龙齿的快速鉴别;黄必胜等;《中国现代中药》;20131231;第15卷(第12期);1046-1049页 * |
| 近红外光谱分析技术在药物质量分析中的应用进展;李真等;《药物评价研究》;20160831;第39卷(第4期);686-692页 * |
| 近红外分析技术在中药鉴定和含量测定中的应用研究进展;战皓等;《中国实验方剂学杂质》;20150630;第21卷(第12期);231-234、封三页 * |
| 近红外漫反射光纤光谱法快速鉴别新疆黑果小檗皮;王庆振等;《安徽医药》;20150630;第19卷(第6期);1074-1076页2方法、3结果和4讨论，图7-13 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107561036A (en) | 2018-01-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Woo et al. | Discrimination of herbal medicines according to geographical origin with near infrared reflectance spectroscopy and pattern recognition techniques | |
| CN104062262A (en) | Crop seed variety authenticity identification method based on near infrared spectrum | |
| CN103364359A (en) | Application of SIMCA pattern recognition method to near infrared spectrum recognition of medicinal material, rhubarb | |
| CN107515203A (en) | The research of near infrared technology quantitative analysis rice single grain amylose content | |
| CN103278473B (en) | The mensuration of pipering and moisture and method for evaluating quality in white pepper | |
| CN105866056A (en) | Hybrid purity identification method based on near infrared spectroscopy | |
| CN104020128B (en) | A kind of method of quick discriminating propolis Jiao Yuan | |
| CN111007032B (en) | Near-infrared spectroscopy for rapidly and nondestructively identifying liquorice and pseudo-product glycyrrhiza spinosa | |
| CN106092990A (en) | A kind of three-dimensional fluorescence spectrum discrimination method of lycium barbarum | |
| CN104730030A (en) | Method for true and false identification and place of origin judgment of codonopsis pilosula based on near infrared analysis technology | |
| CN109490246A (en) | A kind of rapid detection method of root of purple-flowered peucedanum quality of medicinal material | |
| Chen et al. | Fast detection of cumin and fennel using NIR spectroscopy combined with deep learning algorithms | |
| CN109444186A (en) | A kind of pearl powder X-ray diffraction differential method | |
| CN103487422A (en) | Cloud traditional Chinese medicine quality detection system of multi-wavelength LED fluorescence spectrum and method | |
| CN106198442A (en) | A kind of spectroscopic analysis methods differentiating Panjin rice | |
| CN113029999A (en) | Near infrared spectrum identification model construction method and identification method of Zingiberaceae traditional Chinese medicine formula granules | |
| CN107561036B (en) | Rhizoma bletillae variety and authenticity detection method | |
| CN110567907A (en) | Method for rapidly identifying authenticity of traditional Chinese medicine based on infrared spectrum technology | |
| CN106226267B (en) | A kind of near-infrared assay method of dry chili color value | |
| CN111523587A (en) | Woody plant species spectrum identification method based on machine learning | |
| Rajesh et al. | Studies on identification of medicinal plant variety based on NIR spectroscopy using plant leaves | |
| CN113176227A (en) | Method for rapidly predicting adulteration of dendrobium huoshanense in dendrobium hunan | |
| CN203572772U (en) | Cloud traditional Chinese medicine quality detection system based on multi-wavelength LED fluorescence spectrum | |
| CN103076300B (en) | Method for judging and analyzing traditional Chinese medicine resource fingerprint information by specific mode identification model | |
| AU2018101606A4 (en) | A method for identifying meconopsis quintuplinervia regel from different geographical origins |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200228 |